Abstract
Confocal Microwave Imaging algorithms for the early detection of breast cancer are straight-forward to implement using general-purpose computing platforms. However, the large number of radar signals, higher sampling rate and ever-more sophisticated reconstruction algorithms can all significantly slow down the image formation process. This paper focuses on improved computational implementations of Confocal Microwave Imaging algorithms using Graphics Processing Units, in order to accelerate the image formation process. The GPU based implementations have been evaluated by comparing them with both CPU-based sequential implementations and CPU-based parallel implementations. The computational time was reduced by a factor of 250 compared to sequential implementation and a factor of 110 compared to a parallel CPU implementation.
| Original language | English (Ireland) |
|---|---|
| Title of host publication | 2015 9th European Conference on Antennas and Propagation (EuCAP) |
| Publication status | Published - 1 Jan 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Authors (Note for portal: view the doc link for the full list of authors)
- Authors
- Elahi, MA,Shahzad, A,Glavin, M,Jones, E,O'Halloran, M,
Fingerprint
Dive into the research topics of 'GPU Accelerated Confocal Microwave Imaging Algorithms for Breast Cancer Detection'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver